This project consists of several components. One component compares a fixed and a random effects model for combining data from a series of comparative trials. Another component develops and compares parametric and non-parametric tests to assess the assumption of homogeneity of effects in data from a series of trials. A third component considers meta-analytic methods for combining the evidence from a series of HIV seroprevalence studies to estimate HIV prevalence in a target population. The fourth component addresses issues that pertain to the use of meta- analysis in the design and monitoring of clinical trials.